Deep Learning for Automatic Wafer Monitoring System-Reference-Cited by-同舟云学术

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Deep Learning for Automatic Wafer Monitoring System

Published:2023-03-28 Issue: Volume:120 Page:1-6
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Container-title:2023 Smart Systems Integration Conference and Exhibition (SSI)
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Author:

Rundo Francesco¹,Calabretta Michele¹,Pino Carmelo¹,Coffa Salvatore¹,Messina Angelo²,Spampinato Concetto³,Battiato Sebastiano⁴

Affiliation:

1. ADG Power and Discretes R&D Division, STMicroelectronics,Catania,Italy

2. IPA Division, STMicroelectronics,Catania,Italy

3. University of Catania,PerCeiVe Lab Group,Department of Electrical, Electronics and Computer Engineering,Catania,Italy

4. University of Catania,IP-LAB Group,Department of Mathematics and Computer Science,Catania,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10387937/10387754/10387766.pdf?arnumber=10387766

Reference27 articles.

1. Silicon carbide diodes for neutron detection

2. Wafer Map Failure Pattern Recognition and Similarity Ranking for Large-Scale Data Sets

3. AdaBalGAN: An Improved Generative Adversarial Network With Imbalanced Learning for Wafer Defective Pattern Recognition

4. Explainable deep learning for efficient and robust pattern recognition: A survey of recent developments;Bai,2021

5. A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes

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